A two-level adaptive chirp mode decomposition method for the railway wheel flat detection under variable-speed conditions

2021 ◽  
Vol 498 ◽  
pp. 115963
Author(s):  
Shiqian Chen ◽  
Kaiyun Wang ◽  
Chao Chang ◽  
Bo Xie ◽  
Wanming Zhai
Keyword(s):  
Decomposition Method ◽  
Variable Speed ◽  
Railway Wheel ◽  
Mode Decomposition ◽  
Wheel Flat

scholarly journals Railway Wheel Flat Detection Based on Improved Empirical Mode Decomposition

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Yifan Li ◽  
Jianxin Liu ◽  
Yan Wang
Keyword(s):  
Empirical Mode Decomposition ◽  
Vibration Signal ◽  
Railway Wheel ◽  
Mode Decomposition ◽  
Track Irregularity ◽  
Wheel Flat ◽  
Mixing Problem ◽  
Emd Method ◽  
Mode Mixing ◽  
Fault Characteristic

This study explores the capacity of the improved empirical mode decomposition (EMD) in railway wheel flat detection. Aiming at the mode mixing problem of EMD, an EMD energy conservation theory and an intrinsic mode function (IMF) superposition theory are presented and derived, respectively. Based on the above two theories, an improved EMD method is further proposed. The advantage of the improved EMD is evaluated by a simulated vibration signal. Then this method is applied to study the axle box vibration response caused by wheel flats, considering the influence of both track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method is verified by a test rig experiment. Research results demonstrate that the improved EMD can inhibit mode mixing phenomenon and extract the wheel fault characteristic effectively.

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